"Max Gordon"
16 February 2016
| Estimate | 95% CI | |
|---|---|---|
| Median | 0.6 | 0.6 to 0.6 |
| Upper quartile | 1.2 | 1.1 to 1.2 |
| Top 5% | 9.9 | 8.9 to 10.9 |
| Top 1% | 182 | 139 to 225 |
2015
2012-2013
Author: Hadley
library("xml2")
txt <-
"<foo>
<bar> text <baz/>
</bar>
</foo>"
x <- read_xml(txt)
x
{xml_document}
<foo>
[1] <bar> text <baz/> \n </bar>
xml_children(x)
{xml_nodeset (1)}
[1] <bar> text <baz/> \n </bar>
xml_find_all(x, "//baz")
{xml_nodeset (1)}
[1] <baz/>
Author: Csardi & Ooms
library(rversions)
r_release()
version date
97 3.2.3 2015-12-10T08:13:08.415370Z
r_versions() %>%
tail
version date
92 3.1.2 2014-10-31T08:11:32.082768Z
93 3.1.3 2015-03-09T08:12:20.229070Z
94 3.2.0 2015-04-16T07:13:33.144514Z
95 3.2.1 2015-06-18T07:15:04.589869Z
96 3.2.2 2015-08-14T07:13:18.272871Z
97 3.2.3 2015-12-10T08:13:08.415370Z
Author: Stefan Widgren
library(git2r)
repo <- init(".")
commits(repo) %>%
head(3)
[[1]]
[65e26d3] 2016-02-16: Switched to Rpres for better styling
[[2]]
[ff8addf] 2016-02-16: Added a few more details to trends
[[3]]
[024ad5f] 2016-02-15: Added top charts
Author: Iannone, Sveidqvist, Bostock, Pettitt, Daines, Kashcha, Iannone
library(DiagrammeR)
DiagrammeR("
graph LR
A-->B
A-->C
C-->E
B-->D
C-->D
D-->F
E-->F
", height = 200, width = 400)
DiagrammeR::mermaid("
gantt
title A Gantt Diagram
section Section
A task :a1, 2014-01-01, 30d
Another task :after a1 , 20d
section Another
Task in sec :2014-01-12 , 12d
anther task : 24d
", width = 600, height = 250)
| Coder | Total ave. downloads per day | No. of packages | |
|---|---|---|---|
| 1 | Gabor Csardi | 2,312 | 11 |
| 2 | Stefan Widgren | 1,563 | 1 |
| 3 | RStudio | 781 | 16 |
| 4 | Hadley Wickham | 695 | 12 |
| 5 | Jeroen Ooms | 541 | 10 |
| 6 | Richard Cotton | 501 | 22 |
| 7 | R Foundation | 490 | 1 |
| 8 | David Hoerl | 455 | 1 |
| 9 | Sindre Sorhus | 409 | 2 |
| 10 | Richard Iannone | 294 | 2 |
| Coder | Total ave. downloads per day | No. of packages | |
|---|---|---|---|
| 1 | Hadley Wickham | 32,115 | 55 |
| 2 | Yihui Xie | 9,739 | 18 |
| 3 | RStudio | 9,123 | 25 |
| 4 | Jeroen Ooms | 4,221 | 25 |
| 5 | Justin Talbot | 3,633 | 1 |
| 6 | Winston Chang | 3,531 | 17 |
| 7 | Gabor Csardi | 3,437 | 26 |
| 8 | Romain Francois | 2,934 | 20 |
| 9 | Duncan Temple Lang | 2,854 | 6 |
| 10 | Adrian A. Dragulescu | 2,456 | 2 |
| 11 | JJ Allaire | 2,453 | 7 |
| 12 | Simon Urbanek | 2,369 | 15 |
| 13 | Dirk Eddelbuettel | 2,094 | 33 |
| 14 | Stefan Milton Bache | 2,069 | 3 |
| 15 | Douglas Bates | 1,966 | 5 |
| 16 | Renaud Gaujoux | 1,962 | 6 |
| 17 | Jelmer Ypma | 1,933 | 2 |
| 18 | Rob J Hyndman | 1,933 | 3 |
| 19 | Baptiste Auguie | 1,924 | 2 |
| 20 | Ulrich Halekoh Søren Højsgaard | 1,764 | 1 |
| 21 | Martin Maechler | 1,682 | 11 |
| 22 | Mirai Solutions GmbH | 1,603 | 3 |
| 23 | Stefan Widgren | 1,563 | 1 |
| 24 | Edwin de Jonge | 1,513 | 10 |
| 25 | Kurt Hornik | 1,476 | 12 |
| 26 | Deepayan Sarkar | 1,369 | 4 |
| 27 | Tyler Rinker | 1,203 | 9 |
| 28 | Yixuan Qiu | 1,131 | 12 |
| 29 | Revolution Analytics | 1,011 | 4 |
| 30 | Torsten Hothorn | 948 | 7 |
Chair: Hadley W.
From the about page:
Members: Microsoft, RStudio, TIBC, Google, HP, Oracle, …
R-Hub will modernize and improve the entire process of developing and testing R packages
library(dplyr)
library(magrittr)
data_a <-
data.frame(id = 1:3,
var1 = LETTERS[1:3])
data_b <-
data.frame(id = 1:3+2,
var2 = LETTERS[1:3+2])
data_a %>%
left_join(data_b) %>%
knitr::kable()
| id | var1 | var2 |
|---|---|---|
| 1 | A | NA |
| 2 | B | NA |
| 3 | C | C |
data_a %>%
inner_join(data_b) %>%
knitr::kable()
| id | var1 | var2 |
|---|---|---|
| 3 | C | C |
data_a %>%
right_join(data_b) %>%
knitr::kable()
| id | var1 | var2 |
|---|---|---|
| 3 | C | C |
| 4 | NA | D |
| 5 | NA | E |
data_a %>%
anti_join(data_b) %>%
knitr::kable()
| id | var1 |
|---|---|
| 2 | B |
| 1 | A |
data_b %>%
anti_join(data_a) %>%
knitr::kable()
| id | var2 |
|---|---|
| 4 | D |
| 5 | E |
set.seed(98213)
data_c <-
data.frame(id = c(1,1,2,2,3),
var1 = runif(5))
knitr::kable(data_c)
| id | var1 |
|---|---|
| 1 | 0.9736481 |
| 1 | 0.6692199 |
| 2 | 0.7389001 |
| 2 | 0.7678625 |
| 3 | 0.1859028 |
data_c %>%
group_by(id) %>%
filter(var1 == min(var1)) %>%
knitr::kable()
| id | var1 |
|---|---|
| 1 | 0.6692199 |
| 2 | 0.7389001 |
| 3 | 0.1859028 |
# The do allows us to do custom operations
data_c %>%
group_by(id) %>%
do({
if(nrow(.) == 1)
return(.)
.$var1 = min(.$var1) +
max(.$var1)^2
return(.[1,])
}) %>%
knitr::kable()
| id | var1 |
|---|---|
| 1 | 1.6172106 |
| 2 | 1.3285129 |
| 3 | 0.1859028 |
library(multidplyr)
data_d <-
data.frame(id = sample(1:10, size = 10^4, replace = TRUE),
var1 = runif(10^4))
data_d %>%
partition(id) %>%
do({
if(nrow(.) == 1)
return(.)
.$var1 = min(.$var1) +
max(.$var1)^2
return(.[1,])
}) %>%
collect() %>%
arrange(id) %>%
tail(3) %>%
knitr::kable()
| id | var1 |
|---|---|
| 8 | 1.0003005 |
| 9 | 1.0020283 |
| 10 | 0.9981546 |
library(flexsurv)
spl <- flexsurvspline(Surv(recyrs, censrec) ~ group, data=bc, k=1, scale="odds")
## Fitted survival
plot(spl, lwd=3, ci=FALSE)
surv_est <-
data.frame(group = c("Medium", "Poor")) %>%
summary(spl,
newdata = .)
# Generate tidy data
surv_est <-
data.frame(surv_est$`group=Medium`,
group = "Medium") %>%
rbind(data.frame(surv_est$`group=Poor`,
group = "Poor"))
gpl <-
ggplot(surv_est,
aes(x = time, y = est,
group = group, fill = group)) +
geom_ribbon(aes(ymax = ucl, ymin = lcl)) +
geom_line() +
scale_fill_brewer(guide = guide_legend("Group")) +
scale_x_continuous(expand = c(0,0)) +
scale_y_continuous(expand = c(0,0)) +
ylab("Survival") + xlab("Time (years)")